Prescribing trends of proton pump inhibitors and histamine blockers among children in the United Kingdom (1998–2019): A population‐based assessment
Bibliographic record
Abstract
Abstract Purpose To describe the prescribing trends of proton pump inhibitors (PPIs) and H2 receptor antagonists (H2RAs) among children with gastroesophageal reflux in the United Kingdom between 1998 and 2019. Methods We conducted a population‐based retrospective cohort study using data from the Clinical Practice Research Datalink that included all children aged ≤18 years with a first ever diagnosis of gastroesophageal reflux between 1998 and 2019. Using negative binomial regression, we estimated crude and adjusted annual prescription rates per 1000 person‐years and corresponding 95% confidence intervals (CIs) for PPIs and H2RAs. We also assessed rate ratios of PPIs and H2RAs prescription rates to examine changes in prescribing over time. Results Our cohort included 177 477 children with a first ever diagnosis of gastroesophageal reflux during the study period. The median age was 13 years (IQR: 1, 17) among children prescribed PPIs and 0.2 years (IQR: 0.1, 0.6) among those prescribed H2RAs. The total prescription rate of all GERD drugs was 1468 prescriptions per 1000 person‐years (PYs) (95% CI 1463–1472). Overall, PPIs had a higher prescription rate (815 per 1000 PYs, 95% CI 812–818) than H2RAs (653 per 1000 PYs 95% CI 650–655). Sex‐ and age‐adjusted rate ratios of 2019 versus 1998 demonstrated a 10% increase and a 76% decrease in the prescription rates of PPIs and H2RAs, respectively. Conclusions Prescription rates for PPIs increased, especially during the first half of the study period, while prescription rates for H2RA decreased over time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".